• KIISE Transactions on Computing Practices
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• v.21 no.12
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• pp.756-761
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• 2015

With the emergence of the Internet-of-Things (IoT) paradigm, there is a growing demand for personalized services using IoT contexts acquired from heterogeneous IoT devices. However, due to the mismatch between IoT context exchange schemes of context-aware services and IoT devices, IoT applications can acquire IoT contexts only from IoT devices that support the same IoT context exchange schemes. In this paper, we propose dynamic methods to mediate those mismatches on the IoT context exchange schemes. With the proposed mediation methods, context-aware services can collect IoT contexts from heterogeneous IoT devices without considering their IoT context exchange schemes.

• The Mathematical Education
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• v.60 no.1
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• pp.1-19
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• 2021

This study investigates students' conceptions of fractions from a measurement approach while providing a technological environment designed to support students' understanding of the relationships between quantities and adjustable units. 13 third-graders participated in this study and they were involved in a series of measurement tasks through task-based interviews. The tasks were devised to investigate the relationship between units and quantity through manipulations. Screencasting videos were collected including verbal explanations and manipulations. Drawing upon the theory of semiotic mediation, students' constructed concepts during interviews were coded as mathematical words and visual mediators to identify conceptual profiles using a fine-grained analysis. Two students changed their strategies to solve the tasks were selected as a representative case of the two profiles: from guessing to recursive partitioning; from using random units to making a relation to the given unit. Dragging mathematical objects plays a critical role to mediate and formulate fraction understandings such as unitizing and partitioning. In addition, static and dynamic representations influence the development of unit concepts in measurement situations. The findings will contribute to the field's understanding of how students come to understand the concept of fraction as measure and the role of technology, which result in a theory-driven, empirically-tested set of tasks that can be used to introduce fractions as an alternative way.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.711-721
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• 2021

A firm's competitive advantage generating from empowering its dynamic capabilities is very important for established companies and new business ventures in facing intense competition and in responding to unanticipated environmental changes. This study aims to investigate the relationship between dynamic capabilities of a new business venture and its competitive advantage and the effect of entrepreneurial creativity and ambidextrous innovation mediation on the relationship between dynamic capabilities and the competitive advantage of a new business venture. Data was collected using an online survey from 143 new Indonesian shipping agency companies that spread over two-thirds of Indonesia's territory and was analyzed using structural equations modeling (SEM). The results showed that the dynamic capabilities of new business ventures are positively associated with competitive advantage but not significantly. This result indicates that empowering a new business venture's dynamic capability is not sufficient to generate a competitive advantage. However, a new business venture's dynamic capability is significantly and positively associated with the competitive advantage when mediated by entrepreneurial creativity and ambidextrous innovation. The findings of this study suggest that the competitive advantage of a new business venture can be gained from empowering a firm's dynamic capabilities through mediating entrepreneurial creativity and ambidextrous innovation in facing intense competition and in responding to unanticipated environmental changes.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.4
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• pp.175-192
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• 2020

This study analyzed the effects of corporate dynamic capabilities on enterprise performance by using ambidextrous innovation activities as mediators, focusing on SME employees. The sub-variables of dynamic capabilities were divided into opportunity exploration capability, resource acquisition capability, and resource reconstruction capability. 282 questionnaires collected from small and medium-sized enterprises residing in the metropolitan area were used for empirical analysis. SPSS v22.0 and Process macro v3.4 were used to analyze the parallel multiple mediation model. First, the results of the analysis showed that opportunity exploration capability, resource acquisition capability had a positive (+) effect on the ambidextrous innovation activities, and the effect of resource reconstruction capability on ambidextrous innovation activities was not significant. Second, the ambidextrous innovation activities had a significant effect on the enterprise performance. Third, it was found that opportunity exploration capability and resource acquisition capability had a positive (+) effect on enterprise performance, and the effect of resource reconstruction capability on enterprise performance was not significant. Fourth, the ambidextrous innovation activity mediated the relationship between opportunity exploration capability and enterprise performance. Fifth, the ambidextrous innovation activity mediated the relationship between resource acquisition capability and enterprise performance. Sixth, the ambidextrous innovation activity did not mediate the resource reconstruction capability and the enterprise performance. As a follow-up study, it is necessary to find third mediators besides the mediators used in this study, analyze the serial mediation model through these, and study for the moderated mediation analysis through the conditional process model in which the moderator is introduced.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1352-1356
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• 2006

우리나라에서 물과 관련된 분쟁은 민주화와 지방분권화가 가속화됨에 따라 갈등의 주체뿐만 아니라 전개양상까지도 다양하게 변화되고 있다. 최근에는 이 같은 갈등구조가 심화되고, 다양한 형태로 표출됨에 따라 사회불안요인으로까지 확대되고 있어 합리적이고 효율적인 분쟁해결을 지원하기 위한 방법론이 필요한 실정이다. 본 연구에서는 대안적 분쟁해결(ADR, Alternative Dispute Resolution)의 기법 중 하나인 조정(mediation)과정에서의 조정안 도출을 위해 게임이론을 적용하였다. 게임이론에 의한 합리적 해는 제시된 조정안에 객관성을 부여함으로써 의사결정과정의 신뢰성을 향상시킬 것으로 기대된다. 본 연구를 통해 제시한 방법론을 지역 간물 배분과 관련한 가상의 분쟁상황에 적용하였으며, 동적완비정보게임(dynamic complete information game)에서의 교섭게임(bargaining game)으로 구성한 뒤, 경기자(players) 간 배분비율과 배분량을 도출하였고, 이를 편익함수에 의한 양 경기자의 부족편익과 초과편익을 비교하여 그만큼의 편익 차를 보상해주는 조정을 모색하였다. 본 연구는 제3자(third party)에 의한 조정안 제안 시 객관적이고 합리적인 해를 제공하여 이해당사자들이 합의를 이끌어 내는 데 크게 기여할 수 있을 것으로 사료된다.

• The Journal of Korean Physical Therapy
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• v.28 no.4
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• pp.221-226
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• 2016

Purpose: This study was conducted to evaluate the effects of neck and trunk stabilization exercise on static and dynamic balance in older adults. Methods: A total of 30 older adults participated in this study. Participants were randomly assigned to the neck and trunk stabilization exercise group (NTSG) (n=15) or the trunk stabilization exercise group (TSG) (n=15). The NTSG performed a trunk stabilization exercise added to a neck stabilization exercise that included biofeedback. Both groups received training for 30 minutes per day three times per week for eight weeks. The anterior, posterior limit of stability and sway length was used to measure static balance ability, while the timed up and go (TUG) test was used to measure dynamic balance ability. Results: Participants showed significant differences in sway length, anterior limit of stability, posterior limit of stability, and the results of the TUG test between their pre- and post mediation evaluations (p<0.05). The NTSG showed a more significant increase than the TSG (p<0.05). Conclusion: According to the results of this study, both exercises effectively improved static and dynamic balance ability. However, the neck and trunk stabilization exercise is more efficient for increasing the balance ability of older adults.

• The Journal of Korean Physical Therapy
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• v.28 no.1
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• pp.1-7
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• 2016

Purpose: The aim of this study was to evaluate the effect of Bridge exercise with abdominal drawing-in on static and dynamic balance in patients with stroke. Methods: Forty patients with stroke participated in this study. Participation was randomly assigned to the Bridge exercise group (n=20) and the Bridge exercise with abdominal drawing-in group (n=20). A bio-feedback device was used when patients performed the Bridge exercise with abdominal drawing-in. This training was performed without any motion on the patient's spine and upper belly part, and the pressure was held with the biofeedback device as 40-70 mmHg. Both groups received training 30 minutes per day, three times per week, for four weeks. Weight bearing, anterior limit of stability, and posterior limit of stability for static balance ability were measured, and Berg balance scale (BBS), Timed up and go test (TUG) for dynamic balance ability were also measured. Results: Participants showed significant differences between pre- and post-mediation in terms of weight bearing, anterior limit of stability, posterior limit of stability, Berg balance scale, and Timed up and go test (p<0.05). The Bridge exercise with abdominal drawing-in group showed a more significant increase (p<0.05). Conclusion: According to the results of this study, both exercises were effective for improving the static and dynamic balance ability. However we suggest that the Bridge exercise with abdominal drawing-in is more efficient for increasing balance ability in patients with stroke.

• 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.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.321-324
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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 Beaming is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to choose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement loaming is different from supervised teaming in the sense that there is no presentation of input-output pairs as training examples. Furthermore, model-free reinforcement loaming algorithms like Q-learning do not require defining or loaming 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 space 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.

• Asian Journal of Innovation and Policy
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• v.4 no.3
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• pp.328-359
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• 2015

To explain the performance gap between firms in the same industry, this study focuses on innovation. It provides a new framework using the dynamic-capability view based on empirical analysis of domestic businesses. The findings of this study are as follows: First, when the uncertainty and competition intensity in the business environment and the level of innovation have “fit”, it means that when the former goes up, so does the latter. In this regard, when the innovation capability of a firm is high, being “fit” means that the level of innovation is also high. When there was fitting innovation on industrial environment and innovation capacity, companies were able to achieve relatively high performance. Also, it was confirmed that instead of innovation for innovation capacity, innovation for industrial environment led to relatively higher performances of firms.