• 전자공학회논문지 IE
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• v.48 no.4
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• pp.13-18
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• 2011

In this paper, we have examined electrical characteristics of LDO regulator according to the process variation using a 1 ${\mu}m$ 20 V high voltage CMOS process. The electrical analysis of LDO regulator have been performed with three kind of SPICE parameter sets (Typ : typical, FF : fast, SS : slow) by process variation which cause change of SPICE parameter such as threshold voltage and effective channel length of MOS devices. From simulation results, we confirmed that in case of SS type SPICE parameter set, the LDO regulator has 3.6 mV/V line regulation, 0.4 mV/mA load regulation and 0.86 ${\mu}s$ output voltage settling time. And in case of Typ type SPICE parameter set, the LDO regulatorhas 4.2 mV/V line regulation, 0.44 mV/mA load regulation and 0.62 ${\mu}s$ output voltage settling time. Finally, in the FF type SPICE parameter set, the LDO regulator has 7.0 mV/V line regulation, 0.56 mV/mA load regulation and 0.27 ${\mu}s$ output voltage settling time.

• Computational Structural Engineering
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• v.1 no.1
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• pp.87-94
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• 1988

The linerization method as one of the recursive quadratic programming method is applied for the optimal design of a large-scale structure supported by Pshenichny's proof of global convergence of the algorithm and convergence rate estimates. The linearization method transforms all constants of the design problem into an equivalent linearized constraint and employs the active-set strategy. This results in substantial computational savings by reducing the number of sate and adjoint to be solved at every design iteration. The illustrative example of plates with beams supported by columns is the typical one of a large-scale structure to give successful optimum solutions with satisfactory convergence criteria. Hopefully, the method may be applicable to all classes of optimization problems.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.491-498
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• 2003

The advanced computer network technology enables connectivity of computers through an open network environment. There has been growing numbers of security threat to the networks. Therefore, it requires intrusion detection and prevention technologies. In this paper, we propose a network based intrusion detection model using FCM(Fuzzy Cognitive Maps) that can detect intrusion by the DoS attack detection method adopting the packet analyses. A DoS attack appears in the form of the Probe and Syn Flooding attack which is a typical example. The SPuF(Syn flooding Preventer using Fussy cognitive maps) model captures and analyzes the packet informations to detect Syn flooding attack. Using the result of analysis of decision module, which utilized FCM, the decision module measures the degree of danger of the DoS and trains the response module to deal with attacks. For the performance comparison, the "KDD′99 Competition Data Set" made by MIT Lincoln Labs was used. The result of simulating the "KDD′99 Competition Data Set" in the SPuF model shows that the probe detection rates were over 97 percentages.

• Korean Journal of Food Science and Technology
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• v.20 no.6
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• pp.834-839
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• 1988

Physicochemical properties of defatted and 1% palmitic acid reincorporated rice starch were investigated comparing with nondefatted starch. Amylose content of defatted starch was higher than that of nondefatted and reincorporated starch. Transmittance, swelling power and solubility of nondeffated and reincorporated starch exhibited two stage behavior but these behaviors were disappaered by defatting. All starches showed a typical A type in X-ray diffraction but relative crystallinity was decreased by defatting. Also by defatting, peak viscosity and break down of amylogram were disappeared and set back was increased.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.3
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• pp.1-14
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• 2013

In this paper, a finite element analysis technique of rolling stock models for collision-induced derailments was suggested using rolling contacts for wheel-rail interaction. The collision-induced derailments of rolling stock can be categorized into two patterns of wheel-climb and wheel-lift according to the friction direction between wheel flange and rail. The wheel-climb derailment types are classified as Climb-up, Climb/roll-over and Roll-over-C types, and the wheel-lift derailment types as Slip-up, Slip/roll-over and Roll-over-L types. To verify the rolling contact simulations for wheel-rail interaction, dynamic simulations of a single wheelset using Recurdyn of Functionbay and Ls-Dyna of LSTC were performed and compared for the 6-typical derailments. The collision-induced derailment simulation of the finite element model of KHST (Korean High Speed Train) was conducted and verified using the theoretical predictions of a simplified wheel-set model proposed for each derailment type.

• Korean Journal of Cognitive Science
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• v.19 no.1
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• pp.17-39
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• 2008

The present study was conducted to provide Korean word association lists for adults and children which are needed in research area of false memory. Associated words, asso[iation strength, and the proportion of cue set size to the total number of associated words produced through the discrete association technique were compared between the two groups. The data showed that associated words with high strength wert same or similar but associated words with lower strength were various in the two groups. The result that adults produced larger proportion of cue set size than children suggests that adults have more typical and more convergent semantic network than children. The present data will be served as a database useful for the studies to investigate cognitive functions in memory and other related area.

• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.104-112
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• 2016

The Adaboost chooses a good set of features in rounds. On each round, it chooses the optimal feature and its threshold value by minimizing the weighted error of classification. The involved process of classification performs a hard decision. In this paper, we expand the process of classification to a soft fuzzy decision. We believe this expansion could allow some flexibility to the Adaboost algorithm as well as a good performance especially when the size of a training data set is not large enough. The typical Adaboost algorithm assigns a same weight to each training datum on the first round of a training process. We propose a new algorithm to assign different initial weights based on some statistical properties of involved features. In experimental results, we assess that the proposed method shows higher performance than the traditional one.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.10
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• pp.565-572
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• 2004

This paper proposes an expert system which can enhance the accuracy of real-time bus reconfiguration strategy by adopting local minimum tree search method and minimize the spreading effect of the fault by considering totally the operating condition when a main transformer fault occurs in the automated substation. The local minimum tree search method to expand the best-first search method. This method has an advantage which can improve the performance of solution within the limits of the real-time condition. The inference strategy proposed expert system consists of two stages. The first stage determines the switching candidate set by searching possible switching candidates starting from the main transformer or busbar related to the event. And, second stage determines the rational real-time bus reconfiguration strategy based on heuristic rules for the obtained switching candidate set. Also, this paper studies the generalized distribution substation modelling using graph theory and a substation database is designed based on the study result. The inference engine of the expert system and the substation database is implemented in MFC function of Visual C++. Finally, the performance and effectiveness of the proposed expert system is verified by comparing the best-first search solution and local minimum tree search solution based on diversity event simulations for typical distribution substation.

• International Journal of Concrete Structures and Materials
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• v.19 no.1E
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• pp.17-23
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• 2007

In rainy weather, permeable concrete pavement has advantages such as good drainage, increased skid resistance, reduced splash and spray behind vehicles for improving the safety of driving vehicles as well as reduction of the traffic noise. It also contributes to improvement of traffic environment. In this study, the fundamental properties of permeable concrete in accordance with maximum size of aggregate, sand percentage and unit cement content were investigated for practical use of permeable concrete pavement. Although the permeability standard for typical permeable asphalt-concrete pavement is $1{\times}10^{-2}cm/sec$, the researchers determined that the coefficient of permeability of the permeable concrete should be set higher at $1{\times}10^{-1}cm/sec$. Then, the researchers measured the coefficient of permeability, strength, void ratio, and continuous void ratio of the permeable concrete while varying maximum size of the aggregate, sand percentage, unit cement content for detailed analysis. It was found that the void ratio, continuous void ratio, and flexural strength were about 15%, 12%, and 5.0MPa, respectively, when the permeability of the concrete was set at $1{\times}10^{-1}cm/sec$. Given that the maximum size of aggregate was $10{\sim}13mm$, we reached the conclusion that the best mix design for permeable concrete was $0{\sim}20%$ of sand percentage and $380kg/m^3$ of unit cement content.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1236-1239
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• 2002

When we see an object, we usually can say what it is easily even for the case where the object isn't shown in the frontal view. However, it is difficult to believe that all views of every object we have ever seen are fully memorized in our brain. Possibly, when an object is shown, we have some typical views of the object in our brain through our past experience and reconstruct the view to recognize what the presented object is. Non-negative Matrix Factorization (NMF) is one of the methods to extract the basis images from sample data set. The prominent feature of this method is that the reconstructed image is obtained by only additions of the basis images with suitable positive weights. So NMF can be seen more biologically plausible method than any other feature extraction methods such as Vector Quantization (VQ) and principal Component Analysis (PCA). In this paper, we adopt NMF to extract the aspect features from the set of images, which consists of various views of a given object. Some experiments are shown how much well NMF can extract the aspect features than any other methods such as VQ and PCA.