• 한국정보시스템학회지:정보시스템연구
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• 제19권1호
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• pp.79-96
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• 2010

The organizations in the competitive business environment are under pressure of handling internal management processes as well as external supply chain issues. In addition, the paradigm of supply chain management (SCM) has been shifted from static to dynamic problems. For the efficient SCM, organizations should be a RTE (Real Time Enterprises) that views entire supply chains as a single entity. In this paper, the agent system that makes RTE and dynamic supply chains possible is developed. Then, the developed agent system is verified in the TAC SCM(Trading Agent Competition Supply Chain Management) experimental environment and a dashboard is also developed for monitoring management activities of supply chains. The contributions of this paper are as followings. First, unlike the previous agent systems, the suggested agent system in this paper provides autonomy and scalability using SOA. Second, this suggested model for dynamic environment can be applied for the development of software supporting a SCM.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권5호
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• pp.2124-2143
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• 2016

In Long Term Evolution-Advanced (LTE-A) systems, Inter-cell Interference (ICI) is a prominent limiting factor that affects the performance of the systems, especially at the cell edges. Based on the literature, Fractional Frequency Reuse (FFR) methods are known as efficient interference management techniques. In this report, the proposed Dynamic Fractional Frequency Reuse (DFFR) technique improved the capacity and cell edge coverage performance by 70% compared to the Fractional Frequency Reuse (FFR) technique. In this study, an improved power allocation method was adopted into the DFFR technique to reach the goal of not only reducing the ICI mitigation at the cell edges, but also improving the overall capacity of the LTE-A systems. Hence, an improved water-filling algorithm was proposed, and its performance was compared with that of other methods that were considered. Through the simulation results and comparisons with other frequency reuse techniques, it was shown that the proposed method significantly improved the performance of the cell edge throughput by 42%, the capacity by 75%, and the coverage by 80%. Based on the analysis and numerical expressions, it was concluded that the proposed DFFR method provides significant performance improvements, especially for cell edge users.

• 산업공학
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• 제14권1호
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• pp.9-19
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• 2001

Production planning and control system plays an important role in manufacturing companies because it determines all production capacity planning, material procurement planning, and production scheduling which are needed in the process of producing products. Many researches on production planning and control system have been conducted for many manufacturing companies for recent decade. But, a considerable research achievement has mainly been obtained on the forecast-driven production for a make-to-stock and an assemble-to-order. The reason is that there are some hardships such as difficulties of standardizing product information, the frequent changes of design and material, and the unexpected dynamic events that influence the production of customer's order in a make-to-order or an engineering-to-order environments. By these characteristics and their complexities, some studies for production planning and control system in a make-to-order environment are presented recently. In this paper, we present the framework of the hietachical production planning and control for a make-to-order environment with dynamic events. In order to illustrate the usefulness of the proposed framework for a hietachical production planning and control, the information system for a make-to-order production was implemented with the object of the company of producing electricity transformer.

• 로봇학회논문지
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• 제3권4호
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• pp.263-269
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• 2008

Visual odometry is a popular approach to estimating robot motion using a monocular or stereo camera. This paper proposes a novel visual odometry scheme using a stereo camera for robust estimation of a 6 DOF motion in the dynamic environment. The false results of feature matching and the uncertainty of depth information provided by the camera can generate the outliers which deteriorate the estimation. The outliers are removed by analyzing the magnitude histogram of the motion vector of the corresponding features and the RANSAC algorithm. The features extracted from a dynamic object such as a human also makes the motion estimation inaccurate. To eliminate the effect of a dynamic object, several candidates of dynamic objects are generated by clustering the 3D position of features and each candidate is checked based on the standard deviation of features on whether it is a real dynamic object or not. The accuracy and practicality of the proposed scheme are verified by several experiments and comparisons with both IMU and wheel-based odometry. It is shown that the proposed scheme works well when wheel slip occurs or dynamic objects exist.

• 한국컴퓨터정보학회지
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• 제2권1호
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• pp.98-108
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• 1995

• 한국멀티미디어학회논문지
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• 제10권6호
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• pp.799-806
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• 2007

The prototypical smart environment to support the context-aware interactions between user and ubiquitous campus environment based on multi-agent system paradigm is proposed in this paper. In this model, the dynamic Bayesian is investigated to solicit and organize agents to produce information and presentation assembly process in order to allocate the resources for an unseen task across multiple services in a dynamic environment. The user model is used to manage varying user constraints and user preferences to achieve system's goals.

• 한국통신학회논문지
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• 제35권7B호
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• pp.1001-1008
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• 2010

본 논문에서는 해상무선통신환경에서 선박의 위치에 따라 속해있는 네크워크 운영자들 간의 장기간(long-term)의 우선순위(priority) 및 서비스 클래스간의 우선순위 등을 고려한 동적스펙트럼할당(DSA: Dynamic Spectrum Allocation) 알고리즘을 제안한다. 제안한 DSA 알고리즘은 네트워크 운영자간의 각기 다른 서비스 클래스의 트래픽 패턴에 대해서 동적으로 스펙트럼을 공유하고 할당하여, 기존의 고정 스펙트럼 할당방식에 비해 사용자들에게 요구하는 스펙트럼 대역폭을 충분히 제공할 수 있어 서비스 만족율을 향상시킴을 보였다. 따라서 제안한 알고리즘은 해상무선통신환경에서도 스펙트럼 공유와 동적 할당을 통한 운영이 가능함을 보여 육상의 유휴 스펙트럼 자원을 활용할 수 있음을 제시하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.304-306
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• 2003

Oceanic pycnocline depth is usually obtained from in situ measurements. As ocean internal waves occur on and propagate along oceanic pycnocline, it is possible to estimate the depth remotely. This paper presents a method for retrieving pycnocline depth from synthetic aperture radar (SAR) imagery where internal waves are visible. This model is constructed by combining a two-layer ocean model and a nonlinear internal wave model. It is also assumed that the observed groups of internal wave packets on SAR imagery are generated by local semidiurnal tides. Case study in East China Sea shows a good agreement with in situ CTD data.

• 한국정보시스템학회지:정보시스템연구
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• 제13권2호
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• pp.49-64
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• 2004

Recently, SCM(Supply Chain Management) embraces the dynamic environmental changes of the participatory bodies in supply chain. Under this dynamic SCM environment, the selection of supplier and outsourcing company is very important. In their selection, the productivity and expertise of suppliers and outsourcing companies are, of course, to be considered as important factors, but whether or nottheycanmeettheduedateisacritical factor. In particular, this is true because an order-based manufacture ought to have CTP(Capable To Promise). For this purpose, by capitalizing onthevirtualmanufactureundertheSCM, this paper has tried to suggest a new agent system for the selection of supplier and outsourcing company. While performing virtual manufacture based on the integration scheduling, this system acquires the production environment and scheduling information of both suppliers and outsourcing companies on a real-timebasis,thusmakingintegrationschedulingpossible. Also, in order to provetheviabilityofthisstudy,thispaper has selected a specific domain and applied it.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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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.