• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.552-556
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• 2005

이동통신사의 다양한 플랫폼은 콘텐츠 개발회사의 다중개발에 의한 경제적 손실을 발생시키고 경쟁력약화로 이어져 다양한 콘텐츠 개발에 집중하지 못하고 있는 문제점을 안고 있다. 이를 해결하기 위한 방안으로 기존의 무선인터넷 플랫폼 환경을 WIPI(Wireless Internet Platform (or Interoperability) 라는 모바일 표준 플랫폼으로 표준화하게 되었다. WIPI 표준 플랫폼은 다운로드에 의한 DLL(Dynamic Linking Library)을 지원함에 따라 무선망을 통해 동적으로 API (Application Programming Interface)를 추가/갱신하는 기능을 제공한다. 본 논문에서는 메모리 사용을 최소화 및 최적화하여 성능을 개선한 콘텐츠 뷰어를 개발하고, 이를 통해 동적 API 추가 및 갱신 모듈을 구현함으로써 효율적인 WIPI 콘텐츠 제작 환경을 제공하고자 한다.

• Journal of Communications and Networks
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• v.10 no.1
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• pp.38-43
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• 2008

In this paper, adaptive channel borrowing approach fuzzy neural networks for load balancing (ACB-FNN) is presented to maximized the number of served calls and the depending on asymmetries traffic load problem. In a wireless network, the call's arrival rate, the call duration and the communication overhead between the base station and the mobile switch center are vague and uncertain. A new load balancing algorithm with cell involved negotiation is also presented in this paper. The ACB-FNN exhibits better learning abilities, optimization abilities, robustness, and fault-tolerant capability thus yielding better performance compared with other algorithms. It aims to efficiently satisfy their diverse quality-of-service (QoS) requirements. The results show that our algorithm has lower blocking rate, lower dropping rate, less update overhead, and shorter channel acquisition delay than previous methods.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.2
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• pp.52-61
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• 2006

For the detection of moving objects, background subtraction methods are widely used. An adaptive Gaussian mixture model combined with probabilistic learning is one of the most popular methods for the real-time update of the complex and dynamic background. However, probabilistic learning approach does not work well in high traffic regions. In this paper, we Propose a reliable learning method of complex and dynamic backgrounds in high traffic regions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3100-3116
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• 2016

With the rapid development of urban traffic system and fast increasing of vehicle numbers, the traditional centralized ways to generate the source-destination shortest path in terms of travel time(the optimal path) encounter several problems, such as high server pressure, low query efficiency, roads state without in-time updating. With the widespread use of smart cameras in the urban traffic and surveillance system, this paper maps the optimal path finding problem in the dynamic road network to the shortest routing problem in the smart camera networks. The proposed distributed optimal path generation algorithm employs the delay routing and caching mechanism. Real-time route update is also presented to adapt to the dynamic road network. The test result shows that this algorithm has advantages in both query time and query packet numbers.

• Structural Engineering and Mechanics
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• v.35 no.6
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• pp.773-789
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• 2010

It is well known that the analytical vibration characteristic of a cracked beam depends largely on the crack model. In the forward analysis, an improved and simplified approach in modeling discrete open cracks in beams is presented. The effective length of the crack zone on both sides of a crack with stiffness reduction is formulated in terms of the crack depth. Both free and forced vibrations of cracked beams are studied in this paper and the results from the proposed modified crack model and other existing models are compared. The modified crack model gives very accurate predictions in the modal frequencies and time responses of the beams particularly with overlaps in the effective lengths with reduced stiffness. In the inverse analysis, the response sensitivity with respect to damage parameters (the location and depth of crack, etc.) is derived. And the dynamic response sensitivity is used to update the damage parameters. The identified results from both numerical simulations and experiment work illustrate the effectiveness of the proposed method.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10e
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• pp.661-663
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• 2002

This paper introduces a dynamic location management with hierarchical location area, which helps in reducing location update(LU) and paging cost and hence total location management cost. Users are assigned to appropriate location area level utilizing the call-to-mobility ratio(CMR) value. CMR values are calculated each time a user enters a new cell by computing its mobility rate and incoming call rate, which are the two key factors for defining the size of the location area.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.163-167
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• 2003

A novel method for 3-dimensional dynamic analysis of marine slender structure gas been developed by using Euler parameters. The Euler parameter rotation, which is being widely used in aerospace vehicle dynamics and multi-body dynamics, has been applied to elastic structure analysis. Large deformation of flexible slender structures is described by means of Euler parameters. Euler parameter method is implemented effectively in incremental-iterative algorithm for 3D dynamic analysis. The normalization constraint of Euler parameters is efficiently satisfied by means of a sequential updating method.

• Journal of Power System Engineering
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• v.6 no.1
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• pp.96-101
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• 2002

In this paper, we address the problem of controlling an end-effector to track and grab a moving target using the visual servoing technique. A visual servo mechanism based on the image-based servoing principle, is proposed by using visual feedback to control an end-effector without calibrated robot and camera models. Firstly, we consider the control problem as a nonlinear least squares optimization and update the joint angles through the Taylor Series Expansion. And to track a moving target in real time, the Jacobian estimation scheme(Dynamic Broyden's Method) is used to estimate the combined robot and image Jacobian. Using this algorithm, we can drive the objective function value to a neighborhood of zero. To show the effectiveness of the proposed algorithm, simulation results for a six degree of freedom robot are presented.

• Journal of Korean Society for Quality Management
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• v.30 no.4
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• pp.68-77
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• 2002

EM algorithm has good convergence rate for numerical procedures which converges on very small step. In the case of proportion estimation in a mixed distribution which has very big incomplete data or of update of new data continuously, however, EM algorithm highly depends on a initial value with slow convergence ratio. There have been many studies to improve the convergence rate of EM algorithm in estimating the proportion parameter of a mixed data. Among them, dynamic EM algorithm by Hurray Jorgensen and Titterington algorithm by D. M. Titterington are proven to have better convergence rate than the standard EM algorithm, when a new data is continuously updated. In this paper we suggest dynamic EM algorithm and Titterington algorithm for the estimation of a mixed Poisson distribution and compare them in terms of convergence rate by using a simulation method.

• ETRI Journal
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• v.41 no.5
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• pp.574-584
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• 2019

A new Mirai variant found recently was equipped with a dynamic update ability, which increases the level of difficulty for DDoS mitigation. Continuous development of 5G technology and an increasing number of Internet of Things (IoT) devices connected to the network pose serious threats to cyber security. Therefore, researchers have tried to develop better DDoS mitigation systems. However, the majority of the existing models provide centralized solutions either by deploying the system with additional servers at the host site, on the cloud, or at third party locations, which may cause latency. Since Internet service providers (ISP) are links between the internet and users, deploying the defense system within the ISP domain is the panacea for delivering an efficient solution. To cope with the dynamic nature of the new DDoS attacks, we utilized an unsupervised artificial neural network to develop a hierarchical two-layered self-organizing map equipped with a twofold feature selection for DDoS mitigation within the ISP domain.