• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11C
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• pp.1551-1563
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• 2004

This paper proposes a hierarchical approach to shape model ASM using wavelet transform. Local structure model fitting in the ASM plays an important role in model-based pose and shape analysis. The proposed algorithm can robustly find good solutions in complex images by using wavelet decomposition. we also proposed effective method that estimates and corrects object's movement by using Wavelet transform-based hierarchical motion estimation scheme for ASM-based, real-time video tracking. The proposed algorithm has been tested for various sequences containing human motion to demonstrate the improved performance of the proposed object tracking.

• Journal of the Earthquake Engineering Society of Korea
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• v.11 no.2 s.54
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• pp.47-56
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• 2007

In this study, tile performance of a passive tuned mass damper (TMD) and a semi-active tuned mass damper (STMD) was evaluated in terms of seismic response control of elastic and inelastic structures under seismic loads. First, elastic displacement spectra were obtained for the damped structures with a passive TMD, which was optimally designed using the frequency and damping ratio presented by previous study, and with a STMD proposed in this study. The displacement spectra confirm that STMD provides much better control performance than passive md with less stroke. Also, the robustness or the TMD was evaluated by off-tuning the frequency of the TMD to that of the structure. Finally, numerical analyses were conducted for an inelastic structure of which hysteresis was described by Bouc-Wen model and the results indicated that the performance of the passive TMD of which design parameters were optimized for a elastic structure considerably deteriorated when the hysteretic portion or the structural responses increased, while the STMD showed about 15-40% more response reduction than the TMD.

• Journal of KIISE:Databases
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• v.29 no.1
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• pp.1-14
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• 2002

Association rule discovery is a method of mining for the associated item set on large databases based on support and confidence threshold. The discovered association rules can be applied to the marketing pattern analysis in E-commerce, large shopping mall and so on. The association rule discovery makes multiple scan over the database storing large transaction data, thus, the algorithm requiring very high overhead might not be useful in real-time association rule discovery in dynamic environment. Therefore this paper proposes an active candidate set management model based on trigger and incremental update mechanism to overcome non-realtime limitation of association rule discovery. In order to implement the proposed model, we not only describe an implementation model for incremental updating operation, but also evaluate the performance characteristics of this model through the experiment.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.2
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• pp.114-121
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• 2001

A circuit model for active-controlled field emitter array(ACFEA) as an electron source of active-controlled field emission display(ACFED) has been proposed. The ACFEA with hydrogenated amorphous silicon thin-film transistor(a-Si:H TFT) and Spindt-type molibdenum tips (Spindt-Mo FEA) has been fabricated monolithically on the same glass. A-Si:H TFT is used as a control device of field emitters, resulting in stabilizing emission current and lowering driving voltage. The basic model parameters extracted from the electrical characteristics of the fabricated a-Si:H TFT and Spindt-Mo FEA were implemented into the ACFEA model with a circuit simulator SPICE. The accuracy of the equivalent circuit model was verified by comparing the simulated results with the measured one through DC analysis of the ACFEA. The transient analysis of the ACFEA showed that the gate capacitance of FEA along with the drivability of TFT strongly affected the response time. With the fabricated ACFEA, we obtained a response time of 15$mutextrm{s}$, which was enough to make 4bit/color gray scale with the pulse width modulation (PWM).

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.329-344
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• 2023

In this study, we comprehensively analyze the generalization performance of various deep learning-based active sonar target classifiers when applied to small and imbalanced active sonar datasets. To generate the active sonar datasets, we use data from two different oceanic experiments conducted at different times and ocean. Each sample in the active sonar datasets is a time-frequency domain image, which is extracted from audio signal of contact after the detection process. For the comprehensive analysis, we utilize 22 Convolutional Neural Networks (CNN) models. Two datasets are used as train/validation datasets and test datasets, alternatively. To calculate the variance in the output of the target classifiers, the train/validation/test datasets are repeated 10 times. Hyperparameters for training are optimized using Bayesian optimization. The results demonstrate that shallow CNN models show superior robustness and generalization performance compared to most of deep CNN models. The results from this paper can serve as a valuable reference for future research directions in deep learning-based active sonar target classification.

• Journal of the Korea Institute of Military Science and Technology
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• v.4 no.1
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• pp.93-103
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• 2001

A reflection signal in an active sonar using a high frequency is mainly formed of a specular reflection from the surface of an object along with several equivalent scatters inside, which are characterized by the spatial distribution of the highlight on the object. This study analyze the existing echo signal synthesis models eq, random distribution model, equivalent interval distribution model & MUTAHID(Modified Underwater TArget by HIlight Distribution) model for simulated target, and compare the characteristics of the reflected signal synthesis results for each model in various conditions. These highlight distribution models can be efficiently applied to the simulated target signals synthesis of various real systems requiring the echo signal synthesis on the underwater target.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.2
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• pp.198-210
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• 1999

산업 및 통신기술이 급속히 발전함에 따라, 다양한 형태의 침입기법을 통해 클라이언트-서버 구조의 정보 공유 및 서비스 개념으로 운영되는 시스템상에서 중요한 정보에 대한 유출 및 파괴로 인한 역기능이 심각할 정도로 증가하고 있다. 따라서, 정보시스템에서의 정보의 불법유출을 방지하고 문서나 시스템에 대한 불법행위를 감지할 수 있는 감사추적 기법이 요구된다. 이 논문에서는 능동데이타베이스의 능동규칙을 기존 기법보다 효과적으로 침입자를 감지할수 있는 새로운 감사추적 및 분석시스템 모델을 제안하였다. 이 모델은 시스템사용자에 의해서 발생되는 감사자료의 비정상 여부를 판단할수 있는 기법과 유형별 침입자를 감지하는 알고리즘을 제시하여 정상적인 사용자의 이탈된 행동을 판단할 수 있는 바업을 제시한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.321-326
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• 1997

소프트웨어 재사용은 새로운 소프트웨어 개발에 소용되는 시간과 비용을 현저히 감소시켜 소프트웨어 개발환경과 생산성을 향상시키는 방법으로, 소프트웨어 위기를 해결하기 위한 중요한 방법이다. 그러나 소프트웨어 부품을 위한 형식 명세서(formal specification)의 부족, 소프트웨어 재사용에 대한 부정적 심리적인 효과 등의 이유 때문에 현실적으로 재사용이 잘 이루어지고 있지 않다. 이러한 문제들을 해결하기 위해서는 부품의 품질 보증에 관한 연구가 소프트웨어 재사용에 관한 연구 분야에서 최우선적으로 이루어져야 하지만, 기존의 연구들은 일반적으로 설정된 재사용 품질 기준을 표준으로 하였으므로, 사용자의 요구가 복잡하고, 다양화되면서 소프트웨어의 크기, 알고리즘과 구조의 복잡도는 증가있는 변화하는 환경에 능동적으로 대처하지 못하고 있다. 그러므로 본 연구에서는 새로운 부품의 삽입과 기존 부품들의 삭제, 분류 기준의 변경 등의 환경 변화에 능동적으로 대처할 수 있는 적응성이 있는 재사용성 결정 모델을 제안한다. 이 모델은 적응성 있는 재사용 결정 알고리즘을 찾기 위해서 데이터에 숨겨진 패턴들을 발견하는 효율적인 알고 ？遲\ulcorner 제공하는 Rough set 이론을 이용한다.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.2
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• pp.169-176
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• 2005

In this paper, a DC and small-signal AC modeling for the active-clamp, ful1-bridge boost converter is described. Based on the operation principle, the ac part of the converter can be replaced by a dc counterpart. Then, a conceptual equivalent circuit is derived by rearranging the switches. The equivalent circuit for this converter consists of CCM(Continuous conduction mode) boost and DCM(Discontinuous conduction mode) buck converter. The analyses for the equivalent CCM boost and DCM buck converter are done using the model of PWM switch. The theoretical modeling results are confirmed through experiment or SIMPLIS simulation.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06b
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• pp.228-231
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• 2007

ALBM(Adaptive Load Balancing and Management)은 S/W L4 스위치를 포함하는 능동형 클러스터 시스템이다. 이 클러스터 시스템은 확장 가능한 인터넷 서비스와 적응형 부하분산 처리 능력을 제공한다. ALBM 클러스터 시스템을 설계할 때, 우리는 Model-Driven Development Method를 사용하여 메타모델을 설계하였다. 본 논문에서는 클러스터의 구성을 위한 에이전트관리, 정보관리와 같은 기능과 결함내성을 위한 이벤트관리, 알고리즘관리와 같은 기능을 고려하는 메타모델을 제시한다. 이 메타모델의 초점은 클러스터의 구성관리와 결함관리를 클러스터 관리 시스템의 설계에 반영하여, 새롭게 클러스터 시스템을 설계할 때 쉽게 이러한 기능을 가질 수 있도록 지원하는 것이다.