• Restorative Dentistry and Endodontics
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• v.36 no.5
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• pp.397-408
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• 2011

Objectives: This study investigated changes in gene expressions concerning of differentiation, proliferation, mineralization and inflammation using Human-8 expression bead arrays when white Mineral Trioxide Aggregate and calcium hydroxide-containing cement were applied in vitro to human dental pulp cells (HDPCs). Materials and Methods: wMTA (white ProRoot MTA, Dentsply) and Dycal (Dentsply Caulk) in a Teflon tube (inner diameter 10 mm, height 1 mm) were applied to HDPCs. Empty tube-applied HDPCs were used as negative control. Total RNA was extracted at 3, 6, 9 and 24 hr after wMTA and Dycal application. The results of microarray were confirmed by reverse transcriptase polymerase chain reaction. Results: Out of the 24,546 genes, 43 genes (e.g., BMP2, FOSB, THBS1, EDN1, IL11, COL10A1, TUFT1, HMOX1) were up-regulated greater than two-fold and 25 genes (e.g., SMAD6, TIMP2, DCN, SOCS2, CEBPD, KIAA1199) were down-regulated below 50% by wMTA. Two hundred thirty nine genes (e.g., BMP2, BMP6, SMAD6, IL11, FOS, VEGFA, PlGF, HMOX1, SOCS2, CEBPD, KIAA1199) were up-regulated greater than two-fold and 358 genes (e.g., EDN1, FGF) were down-regulated below 50% by Dycal. Conclusions: Both wMTA and Dycal induced changes in gene expressions related with differentiation and proliferation of pulp cells. wMTA induced changes in gene expressions related with mineralization, and Dycal induced those related with angiogenesis. The genes related with inflammation were more expressed by Dycal than by wMTA. It was confirmed that both wMTA and Dycal were able to induce gene expression changes concerned with the pulp repair in different ways.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.2
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• pp.152-159
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• 2013

A structural health monitoring(SHM) technique for locating impact position in a composite plate is presented in this paper. The technique employs a single sensor and spatial focusing properties of time reversal(TR) and inverse filtering(IF). We first examine the focusing effect of back-propagated signal at the impact position and its surroundings through simulation. Impact experiments are then carried out and the localization images are found using the TR and IF signal processing, respectively. Both techniques provide accurate impact location results. Compared to existing techniques for locating impact or acoustic emission source, the proposed methods have the benefits of using a single sensor and not requiring knowledge of material properties and geometry of structures. Furthermore, it does not depend on a particular mode of dispersive Lamb waves that is frequently used in the SHM of plate-like structures.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.3
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• pp.144-151
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• 2005

This paper presents a forecasting technique of the short-term marginal price (SMP) using an Artificial Neural Network (ANN). The SW forecasting is a very important element in an electricity market for the optimal biddings of market participants as well as for market stabilization of regulatory bodies. Input data are organized in two different approaches, time-axis and day-axis approaches, and the resulting patterns are used to train the ANN. Performances of the two approaches are compared and the better estimate is selected by a composition rule to forecast the SMP. By combining the two approaches, the proposed composition technique reflects the characteristics of hourly, daily and seasonal variations, as well as the condition of sudden changes in the spot market, and thus improves the accuracy of forecasting. The proposed method is applied to the historical real-world data from the Korea Power Exchange (KPX) to verify the effectiveness of the technique.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.71-75
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• 2003

오류 역전파 학습 알고리즘을 이용하여 영상 인식에 적용 할 경우에는 은닉층의 노드 수를 경험적으로 설정하므로, 학습시간과 지역최소화 및 정체현상이 발생한다. 그리고 ARTI 알고리즘은 입력 패턴과 저장 패턴간의 측정 방법인 유사성 검증 방법과 경계 변수의 설정에 따라 인식률이 좌우된다. 경계 변수의 값이 크면 입력 패턴과 저장 패턴사이에 약간의 차이만 있어도 새로운 카테고리(Category)로 분류하고, 반대로 경계 변수의 값이 적으면 입력 패턴과 저장 패턴 사이에 많은 차이가 있더라도 유사성이 인정되어 입력 패턴들을 대략적으로 분류한다. 따라서 ART1 알고리즘을 영상 인식에 적용하기 위해서는 경계 변수를 경험적으로 설정하므로 인식률에 부정적인 영향을 갖는 문제점이 있다. 따라서 본 논문에서는 개선된 ART1 알고리즘과 지도 학습 방법을 결합하여 신경망의 은닉층 노드를 동적으로 변화시키는 자가 생성지도 학습 알고리즘을 제안한다. 제안된 신경망에서 입력층과 은닉층의 학습 구조에는 ART1 알고리즘을 개선하여 적용하고, 은닉층과 출력층의 학습 구조에는 은닉층에서 승자로 선택된 노드와 출력층 노드와 연결된 가중치만을 조정하고 Delta-Bar-Delta 알고리즘을 적용한다. 제안된 방법의 학습 성능을 분석하기 위하여 학생증 영상에서 추출한 학번 패턴 분류에 적용한 결과, 기존의 신경망 학습 알고리즘보다 학습 성능이 개선됨을 확인하였다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.1
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• pp.61-65
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• 2010

A commercially available soft PZT wafer that is poled in thickness direction is subjected to longitudinal tensile stress loading in both short and open-circuit conditions. Variations of electric displacement in thickness direction and in-plane strains are measured over time during the loading. Different material responses in the two electrical boundary conditions are explained by the effects of piezoelectrically produced internal electric field on linear material moduli and domain switching mechanisms. Finally, a free energy model of normal distribution is introduced to explain the observed creep behavior, and its predictions are compared with experimental observations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.3
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• pp.585-594
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• 2000

The exact path following of an autonomous mobile robot in a factory and an unreliable environment has many disadvantages in case of a classical control algorithm. In this paper, a neural network control approach based on an error back propagation algorithm is proposed for controlling a mobile robot to follow a line installed on the road. Since not only the three recognized informations from three sensors attached on a mobile robot but also the ten detailed informations in non recognition area are learned with input patterns, a mobile robot moves smoothly an installed line in spite of non perception space. The mobile robot has an effect of error minimization with a short time till a destination. To test an effectiveness of the proposed controller, the two motor velocity changes which is affected from a moving angle change of a mobile robot are simulated with computer.

• Journal of Korean Society of Transportation
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• v.23 no.5 s.83
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• pp.169-176
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• 2005

This paper introduces the dynamic control of acceleration lanes at freeway-ramp junctions. The feasibility of operation with flexible length of acceleration lane was tested with most possible traffic conditions. The operational qualify was also evaluated using average speed and total thru-put at both ramp section and freeway section. A CORSIM microscopic simulation model was used to evaluate the operation quality with a variety or volume conditions and three acceleration lanes, each representing different length categories. In addition, tollgate O-D data including travel times were obtained for two sections on the Gyeong-bu Freeway where an effective merging distance has been largely reduced. Its effect was analyzed and compared to the simulation results. Finally, the effects of acceleration lane are discussed and operational improvement at junctions is presented as research findings.

• The Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1037-1045
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• 1996

In this paper, the parallel model for stereo camera is employed to find the heralding angle and the distance between a leading vehicle and the following vehicle, BART(Binocular Autonomous Research Team vehicle). Two TDNNs (Time Delay Neural Network) such as S-TDNN and A-TDNN are introduced to control BART. S-TDNN controls the speed of the following vehicle while A-TDNN controls the steering angle of BATR. A human drives BART to collect data which are used for training the said neural networks. The trained networks performed the vehicle tracking function satisfactorily under the same driving conditions performed by the human driver. The neural network approach has good portability which decreases costs and saves development time for the different types of vehicles.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07b
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• pp.1129-1133
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• 2004

반도체공정 최적화에 소요되는 시간과 경비를 줄이기 위해 신경망 모델이 개발되고 있다. 주로 역전파 신경망을 이용하여 모델이 개발되고 있으며, 본 연구에서는 Radial Basis Function Network (RBFN)을 이용하여 플라즈마 식각공정 모델을 개발한다. 실험데이터는 유도결합형 플라즈마를 이용한 Silicon Carbide 박막의 식각공정으로부터 수집되었다. 모델개발을 위해 $2^4$ 전인자 (full factorial) 실험계획법이 적용되었으며, 모델에 이용된 식각응답은 식각률과 atomic force microscopy로 측정한 식각표면 거칠기이다. 모델검증을 위해 추가적으로 16번의 실험을 수행하였다. RBFN의 예측성능은 세 학습인자, 즉 뉴런수, width, 초기 웨이트 분포 (initial weight distribution-IWD) 크기에 의해 결정된다. 본 연구에서는 각 학습인자의 영향을 최적화하였으며, IWD의 불규칙성을 고려하여 주어진 학습인자에 대해서 100개의 모델을 발생하고, 이중 최소의 IWD를 갖는 모델을 선택하였다. 최적화한 식각률과 표면거칠기 모델의 RMSE는 각기 26 nm/min과 0.103 nm이었다. 통계적인 회귀모델과 비교하여, 식각률과 표면거칠기 모델은 각기 52%와 24%의 향상된 예측정확도를 보였다. 이로써 RBFN이 플라즈마 공정을 효과적으로 모델링 할 수 있음을 확인하였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1990.10a
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• pp.157-162
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• 1990

기계의 정밀도 향상을 위하여는 기계에 대한 보다 정확한 해석을 요구한다. 그러나 실제 기계 시스템은 마찰, Backlash, Saturation등과 같은 비서형 특 성을 가지고 있어 시스템의 해석 및 제어가 어렵게 된다. 특히, 축, 링크, 기 어, 풀리, 베어링등의 기계요소에서는 마찰로 인해 정밀도가 크게 덜어지고 있어, 마찰에 의한 동특성 및 제어는 많은 연구자들에 의해 관심의 대상이 되어 왔다. 마찰력을 고려한 기계시스템의 운동은 정지상태 근처에서 마찰력 의 변화가 심한 비선형 동특성을 보이고 있어 그 해석에 어려움을 겪고 있 다. 실제 마찰이 저속에서 고급 비선형임에도 불구하고 가장 널리 사용되는 형태의 모델로서 쿨통 마찰을 고려한 운동방정식 조차 비선형성으로 인하여 해석에 어려움이 따르고 있다. 마찰은 오랜동안 연구되어 오면서 Fig.1, Fig2 와 같이 등가선형점성 감쇠, 쿨통마찰, 정적마찰로 모델화되거나 이들의 조 합으로 나타내었다[1-5]. 마찰력은 시간영역에서도 연구되어 Walrath[7]는 Fig.3-a의 속도가 역전되는 지점에서 마찰토오크가 .+-.Tf를 공유하는 문제 를 고려하기 위해, Fig.3-b와 같이 동적마찰모델을 사용하였다. 최근의 연구 로서 Armstrong[7]은 마찰의 위치의존성을 고려한 정확한 마찰모델을 설정 하여 개루프제어에 적용, 좋은 제어특성을 확인하였고, Canudas[8]는 저속영 역에서 overcompensation시 limit cycle과 gain의 관계를 해석하였다.