• Applied Chemistry for Engineering
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• v.10 no.8
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• pp.1155-1160
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• 1999

The screening methodology modeling, dispersion modeling procedures for continuous and instantaneous releases of the gas phase flow from the storage tank and pressure relief valve were considered. This study was performed to develop the screening methodology for prediction and control of hazardous/toxic gas releases by estimating the 1-hr average maximum ground-level concentration of $Cl_2$ gas vs. downwind distance by incorporating source term model including the general/physical properties of released material and release mode of the $Cl_2$ storage tank of the chemical plant facilities, dispersion model, and meteorological/topographical data into the TSCREEN model. As the results of the study, it was found that dispersion modes of the dense gas were affected by the state of the released material, the released conditions, physical-chemical properties of released material, and the released modes (continuous and instantaneous releases), and especially largely affected by initial (depressurized) density of the released material and release emission rate as well as the wind velocity. Especially, this study was considered to release hazardous material as meteorological data. It was thought that this screening methodology can be useful as a preliminary guideline for application of the refined analysis model by developing the generic sliding scale methodology for various senarios selected.

• Tunnel and Underground Space
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• v.11 no.2
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• pp.156-166
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• 2001

A stochastic continuum(SC) modeling technique was developed to simulate the groundwater flow pathway in fractured rocks. This model was developed to overcome the disadvantageous points of discrete fracture network(DFN) modes which has the limitation of fracture numbers. Besides, SC model is able to perform probabilistic analysis and to simulate the conductive groundwater pathway as discrete fracture network model. The SC model was formulated based on the discrete fracture network(DFN) model. The spatial distribution of permeability in the stochastic continuum model was defined by the probability distribution and variogram functions defined from the permeabilities of subdivided smaller blocks of the DFN model. The analysis of groundwater travel time was performed to show the consistency between DFN and SC models by the numerical experiment. It was found that the stochastic continuum modes was an appropriate way to provide the probability density distribution of groundwater velocity which is required for the probabilistic safety assessment of a radioactive waste disposal facility.

• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.29-41
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• 2021

Recently, there are increasing attempts to utilize deep learning methodology in the fashion industry. Accordingly, research dealing with various fashion-related problems have been proposed, and superior performances have been achieved. However, the studies for fashion style classification have not reflected the characteristics of the fashion style that one outfit can include multiple styles simultaneously. Therefore, we aim to solve the multi-label classification problem by utilizing the dependencies between the styles. A multi-label recognition model based on a graph convolution network is applied to detect and explore fashion styles' dependencies. Furthermore, we accelerate model training and improve the model's performance through transfer learning. The proposed model was verified by a dataset collected from social network services and outperformed baselines.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.220-227
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• 2021

PCT (Power Cable Tunnel) and UT (Utility Tunnel), which are non-transport underground infrastructures, are mostly RC (Reinforced Concrete) structures, and their durability decreases due to the deterioration caused by carbonation over time. In particular, since the rate of carbonation varies by use and region, a predictive model based on actual carbonation data is required for individual maintenance. In this study, a carbonation prediction model was developed for non-transport underground infrastructures, such as PCT and UT. A carbonation prediction model was developed using multiple regression analysis and deep neural network techniques based on the actual data obtained from a safety inspection. The structures, region, measurement location, construction method, measurement member, and concrete strength were selected as independent variables to determine the dependent variable carbonation rate coefficient in multiple regression analysis. The adjusted coefficient of determination (Ra2) of the multiple regression model was found to be 0.67. The coefficient of determination (R2) of the model for predicting the carbonation of non-transport underground infrastructures using a deep neural network was 0.82, which was superior to the comparative prediction model. These results are expected to help determine the optimal timing for repair on carbonation and preventive maintenance methodology for PCT and UT.

• Journal of the Korea Computer Industry Society
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• v.5 no.5
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• pp.721-728
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• 2004

OCSP (Online Certificate Status Protocol) server which checks the certificate status provides the real time status verification in the PKI (Public Key Infrastructure) system which is the essential system of certificate. However, OCSP server need the message authentication with the server and client, so it has some shortcomings that has slow response time for the demands of many clients concurrently and has complexity of the mathematical process in the public encryption system. In this research, simulation model of the certificate status vertification server is constructed of the DEVS (Discrete EVent system Specification) formalism. This sever model is constructed to practice the authentication with hash function when certificate is checked. Simulation results shows the results of increase of the certificate status verification speed and decrease of the response time to the client.

• Journal of the Earthquake Engineering Society of Korea
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• v.5 no.5
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• pp.1-11
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• 2001

The purpose of this study is to develop the main program and pre/post processor for the geometric and plastic non-linear analysis of steel jacket structures subjected to wave and earthquake loadings. In this paper, steel jackets are modelled using geometric non-linear space frames and wave loadings re evaluated based on Morrison equation using the linear Airy theory and the fifth Stokes theory. Random wave is generated using JONSWAP spectrum. For earthquake analysis, dynamic analysis is performed using artificial earthquake time history. Also the plastic hinge method is presented for limit analysis of steel jacket. In the companion paper, the pre/post processor is developed and the numerical examples are presented for linear and non-linear dynamic analysis of steel jackets.

• The Journal of the Acoustical Society of Korea
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• v.32 no.2
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• pp.116-123
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• 2013

This paper represents generation of time-varying underwater acoustic channels by performing scattering simulation with time-varying ocean surface and Kirchhoff approximation. In order to estimate the time-varying ocean surface, 1D Pierson-Moskowitz ocean power spectrum and Gaussian correlation function were used. The computed scattering coefficients are applied to the amplitudes of each impulse of BELLHOP simulation result. The scattering coefficients are then compared with measured doppler spectral density of signal components which were scattered from ocean surface and the correlation time used in the Gaussian correlation function was estimated by the comparison. Finally, bit-error-rate and channel correlation simulations were performed with the generated time-varying channel based on passive time-reversal communication scenario.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.5
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• pp.437-450
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• 2014

In this study, we developed a methodology to determine the reference parameter for an aircraft impact induced risk assessment of nuclear power plant (NPP) using finite element impact analysis of containment building. The target structure used to develop the method of reference parameter selection is one of the typical Korean PWR type containment buildings. We composed a three-dimensional finite element model of the containment building. The concrete damaged plasticity model was used for the concrete material model. The steels in the tendon, rebar, and liner were modeled using the piecewise-linear stress-strain curves. To evaluate the correlations between structural response and each candidate parameter, we developed Riera's aircraft impact force-time history function with respect to the variation of the loading parameters, i.e., impact velocity and mass of the remaining fuel. For each force-time history, the type of aircraft is assumed to be a Boeing 767 model. The variation ranges of the impact velocity and remaining fuel percentage are 50 to 200m/s, and 30 to 90%, respectively. Four parameters, i.e., kinetic energy, total impulse, maximum impulse, and maximum force are proposed for candidates of the reference parameter. The wellness of the correlation between the reference parameter and structural responses was formulated using the coefficient of determination ($R^2$). From the results, we found that the maximum force showed the highest $R^2$ value in most responses in the materials. The simplicity and intuitiveness of the maximum force parameter are also remarkable compared to the other candidate parameters. Therefore, it can be concluded that the maximum force is the most proper candidate for the reference parameter to assess the aircraft impact induced risk of NPPs.

• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.7-17
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• 2005

The determination of seismic velocities in refractors for near-surface seismic refraction investigations is an ill-posed problem. Small variations in the computed time parameters can result in quite large lateral variations in the derived velocities, which are often artefacts of the inversion algorithms. Such artefacts are usually not recognized or corrected with forward modelling. Therefore, if detailed refractor models are sought with model based inversion, then detailed starting models are required. The usual source of artefacts in seismic velocities is irregular refractors. Under most circumstances, the variable migration of the generalized reciprocal method (GRM) is able to accommodate irregular interfaces and generate detailed starting models of the refractor. However, where the very-near-surface environment of the Earth is also irregular, the efficacy of the GRM is reduced, and weathering corrections can be necessary. Standard methods for correcting for surface irregularities are usually not practical where the very-near-surface irregularities are of limited lateral extent. In such circumstances, the GRM smoothing statics method (SSM) is a simple and robust approach, which can facilitate more-accurate estimates of refractor velocities. The GRM SSM generates a smoothing 'statics' correction by subtracting an average of the time-depths computed with a range of XY values from the time-depths computed with a zero XY value (where the XY value is the separation between the receivers used to compute the time-depth). The time-depths to the deeper target refractors do not vary greatly with varying XY values, and therefore an average is much the same as the optimum value. However, the time-depths for the very-near-surface irregularities migrate laterally with increasing XY values and they are substantially reduced with the averaging process. As a result, the time-depth profile averaged over a range of XY values is effectively corrected for the near-surface irregularities. In addition, the time-depths computed with a Bero XY value are the sum of both the near-surface effects and the time-depths to the target refractor. Therefore, their subtraction generates an approximate 'statics' correction, which in turn, is subtracted from the traveltimes The GRM SSM is essentially a smoothing procedure, rather than a deterministic weathering correction approach, and it is most effective with near-surface irregularities of quite limited lateral extent. Model and case studies demonstrate that the GRM SSM substantially improves the reliability in determining detailed seismic velocities in irregular refractors.

• Journal of Technology Innovation
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• v.26 no.4
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• pp.199-232
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• 2018

There are increasing needs for understanding and fathoming of business management environment through big data analysis at industrial and corporative level. The research using the company disclosure information, which is comprehensively covering the business performance and the future plan of the company, is getting attention. However, there is limited research on developing applicable analytical models leveraging such corporate disclosure data due to its unstructured nature. This study proposes a text-mining-based analytical model for industrial and firm level analyses using publicly available company disclousre data. Specifically, we apply LDA topic model and word2vec word embedding model on the U.S. SEC data from the publicly listed firms and analyze the trends of business topics at the industrial and corporate levels. Using LDA topic modeling based on SEC EDGAR 10-K document, whole industrial management topics are figured out. For comparison of different pattern of industries' topic trend, software and hardware industries are compared in recent 20 years. Also, the changes of management subject at firm level are observed with comparison of two companies in software industry. The changes of topic trends provides lens for identifying decreasing and growing management subjects at industrial and firm level. Mapping companies and products(or services) based on dimension reduction after using word2vec word embedding model and principal component analysis of 10-K document at firm level in software industry, companies and products(services) that have similar management subjects are identified and also their changes in decades. For suggesting methodology to develop analysis model based on public management data at industrial and corporate level, there may be contributions in terms of making ground of practical methodology to identifying changes of managements subjects. However, there are required further researches to provide microscopic analytical model with regard to relation of technology management strategy between management performance in case of related to various pattern of management topics as of frequent changes of management subject or their momentum. Also more studies are needed for developing competitive context analysis model with product(service)-portfolios between firms.