• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.111-122
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• 2004

The driver's decision making (e.g. route choice) is a typical decision making with an uncertainty. In this paper, we investigate the effect of route guidance information on driver's route choice and learning behavior and analyse the potential of information system in a road network in which traffic flows follow random walk. A Simulation performed focuses on the relationship among the network wide performance, message receiving rates and driver's learning mechanism. We know that at high levels of message receiving rates, the network-wide performance may get worse. However, at low levels of receiving rates, we found that the travel time when guidance information is provided decrease compared to the cases when no pubic information is provided. Also, we found that the learning parameter of the learning mechanism model always changes under nonstationary traffic condition. In addition, learning process of drivers does not converge on any specific value. More investigation is needed to enlarge the scope of the study and to explore more deeply driver's behavior.

• Magazine of the Korea Concrete Institute
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• v.11 no.2
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• pp.241-249
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• 1999

To estimate the compressive strength of concrete more realistically, relative large number of data are necessary. However, it is very common in practice that only limited data are available. The purpose of the present paper is therefore to propose a realistic method to estimate the compressive strength of concrete with limited data in actual site. The Bayesian method of statistical analysis has been applied to the problem of the estimation of compressive strength of concrete. The mean compressive strength is considered as the random parameter and a prior distribution is selected to enable updating of the Bayesian distribution of compressive strength of concrete reflecting both existing data and sampling observations. The updating of the Bayesian distribution with increasing data is illustrated in numerical application. It is shown that by combining prior estimation with information from site observation, more precise estimation is possible with relatively small sampling. It is also seen that the contribution of the prior in determining the posterior distribution depends on its sharpness or flatness in relation to the sharpness or flatness of the likelihood function. The present paper allows more realistic determination of concrete strength in site with limited data.

• International Journal of Precision Engineering and Manufacturing
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• v.2 no.2
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• pp.65-72
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• 2001

The design of multi-stage gear drives is a time-consuming process, since on includes more complicated problems, which are not considered in the design of single-stage gear drives. The designer has th determine the number of reduction stages and the gear ratios of each reduction state. In addition, the design problems include not only the dimensional design but also the configuration design of gear drive elements. There is no definite rule and principle for these types of design problems. Thus the design practices largely depend on the sense and the experiences of the designer , and consequently result in undesirable design solution. We propose a new generalized design algorithm to support the designer at the preliminary design phase of multi-stage gear drives. The proposed design algorithm automates the design process by integrating the dimensional design and the configuration design process. The algorithm consists of four steps. In the first step, a designer determines the number of reduction stage. In the second step. gear ratios se chosen by using the random search method. In the third step, the values of basic design parameter are chosen by using the generate and test method. Then, the values of other dimension, such ad pitch diameter, outer diameter, and face width, are calculated for the configuration design in the final step. The strength and durability of a gear is guaranteed by the bending strength and the pitting resistance rating practices by using the AGMA rating formulas. In the final step, the configuration design is carried out b using the simulated annealing algorithm. The positions of gears and shafts are determined to minimize the geometrical volume(size) of a gearbox, while satisfying spatial constraints between them. These steps are carried out iteratively until a desirable solution is acquired. The propose design algorithm has been applied to the preliminary design of four-stage gear drives in order to validate the availability. The design solution have shown considerably good results in both aspects of the dimensional and the configuration design.

• Korean Journal of Microbiology
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• v.47 no.3
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• pp.263-267
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• 2011

Genomic fingerprinting methods are useful in determining relatedness among bacterial strains. However, random coincidences in sizes of two DNA fragments in two different fingerprints may occur, resulting in erroneous interpretation of relatedness between two bacterial genomes. In this study, I estimated the probability of occurrence of DNA bands of identical size in fingerprints of two unrelated genomes, so that the significance of fingerprint-based estimation of genome relatedness could be analyzed. The probability could be estimated as outputs of a function formulated with the three parameters: the numbers of observed fragments, all possible sizes of fragments and observed fragments common in a given pair of fingerprints. The parameter most instrumental to significance of relatedness estimation was the number of all possible sizes of fragments. To keep the number of coincidentally-common size of fragments below 10, about 200 fragments should be distinguishable in the fingerprints.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.790-799
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• 2010

The Upper Devonian Grossmont Formation in Alberta, Canada reserves an estimated 50 billion cubic meters of bitumen and possess about 1/6 of the total bitumen resources in northern Alberta. However, unlike the overlying Athabasca oil sands, non conventional bitumen resources has not been developed as yet. The carbonate rocks of Grosmont Formation have been subject to various stages of diagenesis, including dolomatization and karstification with a strong effect on the distribution of porosity and permeability, which resulted in highly heterogeneous reservoirs. An extensive fracture logging and mapping was performed on total of six boreholes located in the study area to explore the characteristics of fracture geometry system and the subsurface structures of carbonates reservoir that holds bitumen. Fractal dimension was used as a measure of the statistical homogeneity of the fractured rock masses. The applicability of random Cantor dust, Dc, as a fractal parameter was examined systematically. The statistical homogeneity of fractured carbonates rock masses was investigated in the study area. The structural domains of the rock masses were delineated depthwise according to estimated Dc. The major fracture orientation was dominated by horizontal beddings having dip of $0-20^{\circ}$. Also, fractures having high dip angles existed with relatively low frequency. Three dimensional fracture network modeling for each structural domain has been performed based on fracture orientation and intensity, and some representative conceptual models for carbonates reservoir in the study area has been proposed. The developed subsurface conceptual models will be used to capture the geomechanical characteristics of the carbonates reservoir.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.1-7
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• 2020

The manufacturing process of the resistive variable memory device, which is the based of neuromorphic device, maintained the continuity of vacuum process and applied plasma module suitable for the production of the ReRAM(resistive random access memory) and process technology for the neuromorphic computing, which ensures high integrated and high reliability. The ReRAM device of the oxide thin-film applied to the plasma module was fabricated, and research to improve the properties of the device was conducted through various experiments through changes in materials and process methods. ReRAM device based on TiO₂/TiOx of oxide thin-film using plasma module was completed. Crystallinity measured by XRD rutile, HRS:LRS current value is 2.99 × 10³ ratio or higher, driving voltage was measured using a semiconductor parameter, and it was confirmed that it can be driven at low voltage of 0.3 V or less. It was possible to fabricate a neuromorphic ReRAM device using oxygen gas in a previously developed plasma module, and TiOx thin-films were deposited to confirm performance.

• Journal of Korea Multimedia Society
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• v.14 no.6
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• pp.742-751
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• 2011

This paper presents a robust 3D model hashing dependent on key and parameter by using heat kernel signature (HKS), which is special shape feature descriptor, In the proposed hashing, we calculate HKS coefficients of local and global time scales from eigenvalue and eigenvector of Mesh Laplace operator and cluster pairs of HKS coefficients to 2D square cells and calculate feature coefficients by the distance weights of pairs of HKS coefficients on each cell. Then we generate the binary hash through binarizing the intermediate hash that is the combination of the feature coefficients and the random coefficients. In our experiment, we evaluated the robustness against geometrical and topological attacks and the uniqueness of key and model and also evaluated the model space by estimating the attack intensity that can authenticate 3D model. Experimental results verified that the proposed scheme has more the improved performance than the conventional hashing on the robustness, uniqueness, model space.

• Journal of the Korean Society of Safety
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• v.29 no.6
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• pp.166-171
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• 2014

Nuclear power plants are equipped with the reactor trip system (RTS) and the engineered safety features actuation system (ESFAS) to improve safety on the normal operation. In the event of the design basis accident (DBA), a various of post accident monitor(PAM)systems support to provide important details (e.g. Containment pressure, temperature and pressure of reactor cooling system and core exit temperature) to determine action of main control room (MCR). Operator should be immediately activated for the accident mitigation with the information. Especially, core exit temperature is a critical parameter because the operating mode converts from normal mode to emergency mode when the temperature of core exit reaches $649^{\circ}C$. In this study, uncertainty which was caused by exterior environment, characteristic of thermocouple/connector and accuracy of calibrator/indicator was evaluated in accordance with ANSI-ISA 67.04. The square root of the sum of square (SRSS) methodology for combining uncertainty terms that are random and independent was used in the synthesis. Every uncertainty that may exist in the hardware which is used to measure the core exit temperature was conservatively applied and the associative relation between the elements of uncertainty was considered simultaneously. As a result of uncertainty evaluation, the channel statistical allowance (CSA) of single channel of core exit temperature was +1.042%Span. The range of uncertainty, -0.35%Span ($-4.05^{\circ}C$) ~ +2.08%Span($24.25^{\circ}C$), was obtained as the operating criteria of core exit temperature.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.397-402
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• 2003

This paper proposes an efficient fixed-point (FP) algorithm for improving performances of the independent component analysis (ICA) based on neural networks. The proposed algorithm is the FP algorithm based on Newton method for ICA using the adaptive learning parameters. The purpose of this algorithm is to improve the separation speed and performance by using the learning parameters in Newton method, which is based on the first order differential computation of entropy optimization function. The learning rate and the moment are adaptively adjusted according to an updating state of inverse mixing matrix. The proposed algorithm has been applied to the fingerprints and the images generated by random mixing matrix in the 8 fingerprints of 256${\times}$256-pixel and the 10 images of 512$\times$512-pixel, respectively. The simulation results show that the proposed algorithm has the separation speed and performance better than those using the conventional FP algorithm based on Newton method. Especially, the proposed algorithm gives relatively larger improvement degree as the problem size increases.

• Ocean and Polar Research
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• v.33 no.1
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• pp.1-11
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• 2011

This study describes measurements of fast ice recorded on May 23, 2009, in Kongsfjorden (translated as 'Kongs Fjord'), an inlet on the west coast of Spitsbergen in the Svalbard Archipelago. Seasonal fast ice is an important feature for Svalbard fjords, both in relation to their physical environment and also the local ecosystem, since it grows seaward from the coast and remains in place throughout the winter. Ice thickness, snow, ice properties, and wind speed were measured, while SAR (Synthetic Aperture Radar) data was observed simultaneously observed two times from ALOS-PALSAR (L-band). Measured ice thickness was about 25-35 cm while the thickness of ice floe broken from fast ice was measured as 10-15 cm. Average salinity was 1.9-2.0 ppt during the melting period. Polarimetric data was used to extract H/A/alpha-angle parameters of fast ice, ice floe, snow and glacier, which was classified into 18 classes based on these parameters. It was established that the area of fast ice represents surface scattering which indicates low and medium entropy surface scatters such as Bragg and random surfaces, while fast ice covered with snow belongs to a zone of low entropy surface scattering similar to snow-covered land surfaces. The results of this study will contribute to various interpretations of interrelationships between H/A/alpha parameters and the wave scattering Phenomenon of sea ice.