• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.12
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• pp.605-619
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• 2016

This study aims to figure out effects of the rewards applications receiving a lot of attention recently as mobile advertising using the smartphones. Therefore, this study examines differences of user satisfaction and continued use intention according to a user characteristic, demographic characteristic and rewards application characteristic. The research results are as follow. First, in terms of user satisfaction of the rewards applications, there is a significant difference according to the user gender and existence of the reserved value experience. Second, there is a significant difference in the continued use intention of the applications according to the user type and gender. Third, it is also found that there is an interaction effect between the user gender and existence of the reserved value use experience on the continued use intention. This study is significant in that the results may provide future researchers with practical foundations for marketing strategies to activate the rewards applications.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.9-11
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• 2022

Applying Reinforcement Learning in everyday applications and varied environments has proved the potential of the of the field and revealed pitfalls along the way. In robotics, a learning agent takes over gradually the control of a robot by abstracting the navigation model of the robot with its inputs and outputs, thus reducing the human intervention. The challenge for the agent is how to implement a feedback function that facilitates the learning process of an MDP problem in an environment while reducing the time of convergence for the method. In this paper we will implement a reward shaping system avoiding sparse rewards which gives fewer data for the learning agent in a ROS environment. Reward shaping prioritizes behaviours that brings the robot closer to the goal by giving intermediate rewards and helps the algorithm converge quickly. We will use a pseudocode implementation as an illustration of the method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.189-195
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• 2005

One of the major components of any pervasive system is its proactive behavior. Various models have been developed to provide system wide changes which would enable proactive behavior. A major drawback of these approaches is that they do not address the need to make use of existing applications without modifying the applications. To overcome this drawback, a middleware architecture called 'Concord' is proposed. Concord is based on a simple model which consists of Lookup Server and Database. The rewards for this simple model are many. First, Concord uses the existing computing infrastructure. Second, Concord standardizes the interfaces for all services and platforms. Third, new services can be added dynamically without any need for reconfiguration. Finally, Concord consists of Database that can maintain and publish the active set of available resources. Thus Concord provides a solid system for integration of various entities to provide seamless connectivity and enable proactive behavior.

• Nuclear Engineering and Technology
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• v.56 no.6
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• pp.1959-1974
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• 2024

Nuclear energy plays a crucial role in energy supply in the 21st century, and more and more Nuclear Power Plants (NPPs) will be in operation to contribute to the development of human society. However, as a typical complex system engineering, the operation and development of NPPs require efficient and stable control methods to ensure the safety and efficiency of nuclear power generation. Reinforcement learning (RL) aims at learning optimal control policies via maximizing discounted long-term rewards. The reward-oriented learning paradigm has witnessed remarkable success in many complex systems, such as wind power systems, electric power systems, coal fire power plants, robotics, etc. In this work, we try to present a systematic review of the applications of RL on these complex systems, from which we believe NPPs can borrow experience and insights. We then conduct a block-by-block investigation on the application scenarios of specific tasks in NPPs and carried out algorithmic research for different situations such as power startup, collaborative control, and emergency handling. Moreover, we discuss the possibilities of further application of RL methods on NPPs and detail the challenges when applying RL methods on NPPs. We hope this work can boost the realization of intelligent NPPs, and contribute to more and more research on how to better integrate RL algorithms into NPPs.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.199-202
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• 2001

This article deals with stochastic reliability systems that include a repair facility and unreliable machines: the main facility of working and an auxiliary facility of "super-reserve" machines. The number of super-reserve machines are random number with a arbitrarily distribution and working machines break down exponentially. Defective machines line up for repair, whose durations are arbitrarily distributed. Refurbished machines return to the main facility. If the main facility is restored to its original quantity, the repair facility leaves on routine maintenance until all of super-reserve machines are exhausted. Then, the busy period is regenerated. The whole system also falls into the category of closed queues, with more options than those of basic models. The techniques include two-variate Markov and semi-regenerative processes, and a duality principle, to find the probability distribution of the number of intact machines. Explicit formulas obtained demonstrate a relatively effortless use of functionals of the main stochastic characteristics (such as expenses due to repair, maintenance, waiting, and rewards for higher reliability) and optimization of their objective function. Applications include computer networking, human resources, and manufacturing processes.

• International Journal of Knowledge Content Development & Technology
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• v.7 no.2
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• pp.5-20
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• 2017

The notion of object oriented analysis and design in software engineering has many rewards that aid the programmer to have an understanding of and improve the program efficaciously. Object oriented metrics helps rather a lot to a programmer or developer to comprehend and unravel the thing-oriented trouble readily and exactly. Object oriented metrics helps in examining the usefulness of object oriented applied sciences or in simple phrases Object-oriented metrics depict characteristics of object-oriented programming. The intention of this paper is to have an understanding of concerning the UML, Object oriented evaluation and design and the way it plays in UML.

• ETRI Journal
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• v.43 no.6
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• pp.1004-1012
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• 2021

The collaboration productively interacting between multi-agents has become an emerging issue in real-world applications. In reinforcement learning, multi-agent environments present challenges beyond tractable issues in single-agent settings. This collaborative environment has the following highly complex attributes: sparse rewards for task completion, limited communications between each other, and only partial observations. In particular, adjustments in an agent's action policy result in a nonstationary environment from the other agent's perspective, which causes high variance in the learned policies and prevents the direct use of reinforcement learning approaches. Unexpected social loafing caused by high dispersion makes it difficult for all agents to succeed in collaborative tasks. Therefore, we address a paradox caused by the social loafing to significantly reduce total returns after a certain timestep of multi-agent reinforcement learning. We further demonstrate that the collaborative paradox in multi-agent environments can be avoided by our proposed effective early stop method leveraging a metric for social loafing.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.948-956
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• 2016

Many franchise stores are in the surrounding. These stores offer many membership services. But, small traders do not provide much customer management service. For example, non-franchised cafes provide the services through paper coupons. However, most of paper coupons are available only in one store that issued the coupon. Besides, these coupons are in stamp format. Due to the absence of customers' management service, it is hard for small traders to attract customers compared to the franchise. Therefore, in this paper, We had implemented a mobile application, and applied to new customer management service in order to increase the price competitiveness of small traders. This service issues electronic coupon through a mobile app. customers can receive a relatively large amount of discount, and a deadline of coupons are short. When customers use coupons, new coupons are issued at the same time. This structure can be powerful means to lead customers' frequent visit. Small traders can gain a lot of regular customers by using this service.

• Journal of Information Technology Applications and Management
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• v.23 no.2
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• pp.29-59
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• 2016

These days, the business environment such as Information Technology (IT) is rapidly changing, and organizations are consistently trying to change themselves for the survival and success under the changing environment. In this situation, change management is very important because it draws the change behaviors of organization members for the success of organizational change. The purpose of this study is to investigate the effect of the organization members' psychological factors on the performance of the acquisition of new IT, which is one of the most important organizational change. Based on previous studies in the area of organizational change, organization members' resistance to change, self-congruity theory, change activities and organizational performance, the research model is developed for validating the effect of organization members' self-congruity on the performance of the acquisition of new IT. Statistical analyses show that self-congruity has a significant effect on the change activities. In particular, private self-congruity has more impact on the change activities than public self-congruity. In addition, self-leadership, rewards and recognitions, and the diffusion of change activities have significant effects on job satisfaction. Self-leadership has a significant effect on organizational commitment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2202-2217
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• 2012

The transmission opportunities between nodes in Delay Tolerant Network (DTNs) are uncertain, and routing algorithms in DTNs often need nodes serving as relays for others to carry and forward messages. Due to selfishness, nodes may ask the source to pay a certain reward, and the reward may be varying with time. Moreover, the reward that the source obtains from the destination may also be varying with time. For example, the sooner the destination gets the message, the more rewards the source may obtain. The goal of this paper is to explore efficient ways for the source to maximize its total reward in such complex applications when it uses the probabilistic two-hop routing policy. We first propose a theoretical framework, which can be used to evaluate the total reward that the source can obtain. Then based on the model, we prove that the optimal forwarding policy confirms to the threshold form by the Pontryagin's Maximum Principle. Simulations based on both synthetic and real motion traces show the accuracy of our theoretical framework. Furthermore, we demonstrate that the performance of the optimal forwarding policy with threshold form is better through extensive numerical results, which conforms to the result obtained by the Maximum Principle.