• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1061-1065
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• 2004

The knowledge-based society of the 21st century requires effective education and learning methods in each professional field because the development of human resource determines its competence more than any other factors. It is highly desirable to develop an intelligent tutoring system, which meets ever increasing demands of education and learning. Such a system should be adaptive to each individual learner's demands as well as the continuously changing state of the learning process, thus enabling the effective education. The development of a learning environment based on learner modeling is necessary in order to be adaptive to individual learning variants. An intelligent learning environment is being developed targeting the heritage education, which is able to provide a customized and refined learning guide by storing the content of interactions between the system and the learner, analyzing the correlations in learning situations, and inferring the learning preference from the learner's learning history. This paper proposes a heritage learning system of Bulguksa temple, integrating the ontology-based learner modeling and the learning preference which considers perception styles, input and processing methods, and understanding process of information.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.931-934
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• 2005

This paper describes an adaptive recommendation system that provides real-time personalized trading advice to the investors based on their profiles and trading information environment. A proposed system integrates Stochastic technical analysis and artificial neural network that incorporates an adaptive user modeling. The user model is constructed and updated based on initial user profile and recorded user interactions with the system. The information presented to each individual user is also tailor-made to fit the user's behavior and preference. A system prototype was implemented in JAVA. Experiments used to evaluate the system's performance were done on both human subjects and synthetic users. The results show our proposed system is able to rapidly learn to provide appropriate advice to different types of users.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05b
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• pp.1161-1164
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• 2003

본 논문은 ALAN(Application Level Active Network)상에서 GME(Generic Modeling Environment)라고 불리는 컴포지션 메커니즘을 이용하는 AWCS(Adaptive Web Caching Service)에 관하여 언급하였다. ALAN상의 웹 캐싱의 요구사항은 자치 구성성(self-configuration)과 자치 적응성(self-adaptation)이다 이러한 요구사항을 지원하기 위해서 본 논문에서는 친AN상에서 IN(Intelligent Inetwork)에서 유래된 SCE(Service Creation Environment)와 유사한 서비스 컴포지션 메커니즘인 GME를 이용하여 AWCS 의 설계 및 구현에 관하여 언급하였다

• Journal of Korea Multimedia Society
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• v.15 no.3
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• pp.398-407
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• 2012

We propose a tree modeling method of expressing realistically and efficiently numerous trees distributed on a broad terrain. This method combines and simplifies the recursive hierarchy of tree branch and branch generation process through self-organizing from buds, allowing users to generate trees that can be used more intuitively and efficiently. With the generation process the leveled structure and the appearance such as branch length, distribution and direction can be controlled interactively by user. In addition, we introduce an environment-adaptive model that allows to grow a number of trees variously by controlling at the same time and we propose an efficient application method of growing environment. For the real-time rendering of the complex tree models distributed on a broad terrain, the rendering process, the LOD(level of detail) for the branch surfaces, and shader instancing are introduced through the GPU(Graphics Processing Unit). Whether the numerous trees are expressed realistically and efficiently on wide terrain by proposed models are confirmed through simulation.

• Transactions of The Korea Fluid Power Systems Society
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• v.4 no.2
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• pp.1-6
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• 2007

During the last few decades, excavation automation has been investigated to protect the operator from the hazardous working environment and to relieve the cost of the skilled operator. Therefore, a number of modelling and controller design methods of the hydraulic excavator are proposed in many literatures to realize the excavation automation. In this article, a geometric approach far the multi-body system modeling is adopted to develop the excavator mechanism model that contains 4 kinematic loops and 12 links. Considering a simple soil mechanism model with a number of uncertain soil parameters, an adaptive trajectory tracking control strategy based on the developed excavator model is proposed. The improved performance of the designed controller over the simple PID controller is validated via the simulation study.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.372-378
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• 2015

Background subtraction is the first processing stage in video surveillance. It is a general term for a process which aims to separate foreground objects from a background. The goal is to construct and maintain a statistical representation of the scene that the camera sees. The output of background subtraction will be an input to a higher-level process. Background subtraction under dynamic environment in the video sequences is one such complex task. It is an important research topic in image analysis and computer vision domains. This work deals background modeling based on modified adaptive Gaussian mixture model (GMM) with three temporal differencing (TTD) method in dynamic environment. The results of background subtraction on several sequences in various testing environments show that the proposed method is efficient and robust for the dynamic environment and achieves good accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.588-588
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• 1991

This paper proposes a compliance robot control algorithm using fuzzy adaptive controller and fuzzy compliance vector generator. In the compliance robot control, we need more adaptivity because the linear modeling in robot dynamics is getting more difficult by contact with external environment. Existing adapitive controllers have difficulty in realtime processing. So in order to overcome it, We adopt fuzzy adaptive controller and propose fuzzy compliance vector generator for flexible compliant motion. We analyze and confirm the proposed algorithm by surface processing experiment with a control system implemented by VME system.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.2
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• pp.83-91
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• 2018

With the development of IT (Information Technology) technology, embedded system and network technology are combined and used in various environments such as military environment as well as everyday life. In this paper, we propose a new airdropped distributed mobility model (ADMM) modeling the dispersion falling of the direct shot of a cluster bomb, and we compare and analyze some representative MANET routing protocols in ADMM in ns-3 simulator. As a result of the analysis, we show OLSR routing protocol is promising in ADMM environment in the view points of packet delivery ratio (PDR), end to end delay, and jitter. In addition, we propose a new adaptation scheme for OLSR, AND-OLSR (Average Node Distance based adaptive-OLSR) to improve the original OLSR in ADMM environment. The new protocol calculates the average node distance, adapts the period of the control message based on the average node distance increasing rate. Through the simulation study, we show that the proposed AND-OLSR outperforms the original OLSR in PDR and control message overhead.

• The Journal of the Acoustical Society of Korea
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• v.34 no.3
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• pp.177-183
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• 2015

This paper proposes a robust nonlinear acoustic echo canceller (NAEC) which is effective for modeling the nonlinearity of a speaker module and the long acoustic echo path within a speech communication environment. The proposed NAEC utilizes a sigmoid pre-processor for modeling the speaker nonlinearity and a partitioned block frequnecy-domain adaptive filter for identifying the acoustic echo path with small delay. Simulation results confirmed that the proposed algorithm achieves excellent performance with much lower computational complexity than the previous NAEC.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.73-81
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• 2011

In this paper, an improved block-based background modeling technique using adaptive parameter estimation that judiciously adjusts the number of model histograms at each frame sequence is proposed. The conventional block-based background modeling method has a fixed number of background model histograms, resulting to false negatives when the image sequence has either rapid illumination changes or swiftly moving objects, and to false positives with motionless objects. In addition, the number of optimal model histogram that changes each type of input image must have found manually. We demonstrate the proposed method is promising through representative performance evaluations including the background modeling in an elevator environment that may have situations with rapid illumination changes, moving objects, and motionless objects.